This research proposes a cost-effectiveness study of matching and mismatching for patients randomly assigned to alcoholism treatment (12- step facilitation; cognitive-behavioral therapy; motivational enhancement). By comparing client health care utilization and costs for 12 months prior to treatment with those incurred during treatment and throughout 36 months after treatment, the cost-evaluation study will identify dollar cost implications of proper patient match to treatment condition. Two of nine clinical research units (CRUs) from Project MATCH will collaborate with PIRE researchers in the cost-effectiveness study - the Wisconsin CRU (200 outpatient cases and 75 aftercare cases) and the Brown CRU (200 aftercare cases). A total of 475 clients will be recruited as subjects for the study. In addition to the basic MATCH protocol including interviews at intake, after completion of three months of treatment, and every three months for the first year after treatment is completed, cost-offset study subjects will be asked to (1) provide more detailed retrospective accounts of their health care utilization, (2) participate in an extended follow-up period of interviews every three months throughout the second and third year after completing treatment (two years beyond the planned follow-up of MATCH patients), and (3) authorize release of health insurance or health care provider records containing costs associated with health care utilization. For the Brown CRU, detailed health care utilization and extended follow-up periods have already been implemented for MATCH patients as part of a separate supplemental NIAAA-funded R09 study, so only the PIRE follow-up of health care costs from provider or insurance claim records have been added to the current Brown CRU study. Analysis of provider and claims records will more accurately identify diagnoses, dates of occurrences and costs associated with health care use for the cost-offset study of matching. Cost-effectiveness analysis will calculate the net and marginal reductions in health care costs associated with matching adn mismatching. Analysis of variance (ANOVA), analysis of repeated moving average (ARIMA), and econometric time-series analysis models will be used to study these effects over time.